Fast method for reconstruction of 3D coordinates

Bolecek, Libor; Ricny, V.; Slanina, Martin

doi:10.1109/tsp.2012.6256395

Cited by 3 publications

(2 citation statements)

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“…The user can select some points in an empty region. The corresponding point for the selected point can be found by using the method proposed in our paper [10].…”

Section: Concept Of the Methodsmentioning

confidence: 99%

The estimation of a depth map using spatial continuity and edges

Bolecek

Ricny

2013

2013 36th International Conference on Telecommunications and Signal Processing (TSP)

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This paper deals with creating depth maps from two images. The initial map is created using the sum of the absolute differences of the each image point's neighborhood. Many discontinuities are in this map. Therefore, we have to use some approach for its improvement. The proposed method utilizes a combination of a few approaches. The first approach is based on the assumption of continuity of the depth map in rows and utilizing information about edges in images. We designed rules for filling zero areas in the initial depth map. The second step uses disparity of significant points found in zero areas. The significant points are found by the algorithm Speeded Up Robust Features (SURF). The applicability of the proposed method is demonstrated on a few images from Middlebury Stereo Datasets. In the future, we will execute subjective tests for examining the influence of the depth map to the evaluation of the spatial effect. The proposed methods will be used as tool for depth maps generation with various quality.

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“…The user can select some points in an empty region. The corresponding point for the selected point can be found by using the method proposed in our paper [10].…”

Section: Concept Of the Methodsmentioning

confidence: 99%

The estimation of a depth map using spatial continuity and edges

Bolecek

Ricny

2013

2013 36th International Conference on Telecommunications and Signal Processing (TSP)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The ground truth disparity map is the inverse of the ground truth distance scale by the image resolution and the focal length. Equation (8) shows how to calculate the ground truth disparity map from the depth map [18]. The depth map is a 16 bit map with values ranging from 0 to 1 where the ground plane was at D ϭ 1 and the cameras were at D ϭ 0.…”

Section: / /mentioning

confidence: 99%